Learning to Guide a Saturation-Based Theorem Prover
Author:
Affiliation:
1. IBM Research, Armonk, NY, USA
2. Arizona State University, Tempe, AZ, USA
3. Samsung AI, Cambridge, U.K.
4. University of Auckland, Auckland, New Zealand
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Applied Mathematics,Artificial Intelligence,Computational Theory and Mathematics,Computer Vision and Pattern Recognition,Software
Link
http://xplorestaging.ieee.org/ielx7/34/9970415/09669114.pdf?arnumber=9669114
Reference76 articles.
1. Automated theorem proving, fast and slow;rawson;EasyChair Preprint,2021
2. A Neurally-Guided, Parallel Theorem Prover
3. Property invariant embedding for automated reasoning;olšák;Proc 24th Eur Conf Artif Intell,2020
4. Learning representations of logical formulae using graph neural networks;glorot,2019
5. Progress in the Development of Automated Theorem Proving for Higher-Order Logic
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